Computational Methods for Estimating the Size and Identifying the Members of Microbial Communities

C. Putonti, V. Fofanov, and Y. Fofanov (USA)


Biological issues, microbial community analysis, estimating effective genome size, identifying microbial community members.


Environmental samples often contain many various organisms, e.g. protozoa, microbes and viruses, which function together through complex interactions. Identifying the members of a community is challenging due to the fact that members are often dependent upon each other and thus cannot be isolated and cultivated independently. Traditionally, sequencing has been used in order to estimate the size, diversity and members within the sample. This, however, can be both costly and time consuming. Recently, we analyzed numerous viral, microbial, and multi-cellular genomic sequences and observed that the presence of subsequences, of an appropriate length, in different genomes can be treated as a nearly random and independent process where the length of the subsequences directly corresponds to the length of the genomic sequence. These observations suggest that randomly selected primer and/or probe sequences can be used to estimate the effective genomic size of a microbial community as well as identify members of the community in a cost effective, high throughput method. In silico and in vivo results are provided.

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